In [1]:
import plotly
plotly.offline.init_notebook_mode()
import cufflinks as cf
cf.go_offline()
In [21]:
from plotly.graph_objs import Bar,Layout, Figure,Data,Scattermapbox,Marker,Surface,XAxis,YAxis,ZAxis,Scene
In [19]:
import pandas as pd
import numpy as np
In [3]:
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv")
In [4]:
schools = df.School
schools[0]
Out[4]:
'MIT'
In [5]:
df.std()
Out[5]:
Women    12.813683
Men      25.705289
Gap      14.137084
dtype: float64
In [8]:
data = [Bar(x=df.School,
            y=df.Gap)]
In [9]:
plotly.offline.iplot(data)
In [11]:
trace_women = Bar(x=df.School,
                  y=df.Women,
                  name='Women',
                  marker=dict(color='#ffcdd2'))

trace_men = Bar(x=df.School,
                y=df.Men,
                name='Men',
                marker=dict(color='#A2D5F2'))

trace_gap = Bar(x=df.School,
                y=df.Gap,
                name='Gap',
                marker=dict(color='#59606D'))

data = [trace_women, trace_men, trace_gap]
layout = Layout(title="Average Earnings for Graduates",
                xaxis=dict(title='School'),
                yaxis=dict(title='Salary (in thousands)'))
fig = Figure(data=data, layout=layout)
plotly.offline.iplot(fig)
In [12]:
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/Nuclear%20Waste%20Sites%20on%20American%20Campuses.csv')
In [16]:
site_lat = df.lat
site_lon = df.lon
locations_name = df.text

data = Data([
    Scattermapbox(
        lat=site_lat,
        lon=site_lon,
        mode='markers',
        marker=Marker(
            size=17,
            color='rgb(255, 0, 0)',
            opacity=0.7
        ),
        text=locations_name,
        hoverinfo='text'
    ),
    Scattermapbox(
        lat=site_lat,
        lon=site_lon,
        mode='markers',
        marker=Marker(
            size=8,
            color='rgb(242, 177, 172)',
            opacity=0.7
        ),
        hoverinfo='none'
    )]
)
        
layout = Layout(
    title='Nuclear Waste Sites on Campus',
    autosize=True,
    hovermode='closest',
    showlegend=False,
    mapbox=dict(
        accesstoken=mapbox_access_token,
        bearing=0,
        center=dict(
            lat=38,
            lon=-94
        ),
        pitch=0,
        zoom=3,
        style='light'
    ),
)

fig = dict(data=data, layout=layout)
plotly.offline.iplot(fig)
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-16-80e71e16de28> in <module>()
     35     showlegend=False,
     36     mapbox=dict(
---> 37         accesstoken=mapbox_access_token,
     38         bearing=0,
     39         center=dict(

NameError: name 'mapbox_access_token' is not defined
In [22]:
s = np.linspace(0, 2 * np.pi, 240)
t = np.linspace(0, np.pi, 240)
tGrid, sGrid = np.meshgrid(s, t)

r = 2 + np.sin(7 * sGrid + 5 * tGrid)  # r = 2 + sin(7s+5t)
x = r * np.cos(sGrid) * np.sin(tGrid)  # x = r*cos(s)*sin(t)
y = r * np.sin(sGrid) * np.sin(tGrid)  # y = r*sin(s)*sin(t)
z = r * np.cos(tGrid)                  # z = r*cos(t)

surface = Surface(x=x, y=y, z=z)
data = Data([surface])

layout = Layout(
    title='Parametric Plot',
    scene=Scene(
        xaxis=XAxis(
            gridcolor='rgb(255, 255, 255)',
            zerolinecolor='rgb(255, 255, 255)',
            showbackground=True,
            backgroundcolor='rgb(230, 230,230)'
        ),
        yaxis=YAxis(
            gridcolor='rgb(255, 255, 255)',
            zerolinecolor='rgb(255, 255, 255)',
            showbackground=True,
            backgroundcolor='rgb(230, 230,230)'
        ),
        zaxis=ZAxis(
            gridcolor='rgb(255, 255, 255)',
            zerolinecolor='rgb(255, 255, 255)',
            showbackground=True,
            backgroundcolor='rgb(230, 230,230)'
        )
    )
)

fig = Figure(data=data, layout=layout)
plotly.offline.iplot(fig)
In [23]:
data = [dict(
        visible = False,
        line=dict(color='00CED1', width=6),
        name = '𝜈 = '+str(step),
        x = np.arange(0,10,0.01),
        y = np.sin(step*np.arange(0,10,0.01))) for step in np.arange(0,5,0.1)]
data[10]['visible'] = True

steps = []
for i in range(len(data)):
    step = dict(
        method = 'restyle',
        args = ['visible', [False] * len(data)],
    )
    step['args'][1][i] = True # Toggle i'th trace to "visible"
    steps.append(step)

sliders = [dict(
    active = 10,
    currentvalue = {"prefix": "Frequency: "},
    pad = {"t": 50},
    steps = steps
)]

layout = dict(sliders=sliders)
fig = dict(data=data, layout=layout)
plotly.offline.iplot(fig)